Comparison with state-of-the-art.
Table REF  shows the mean Intersection of Union (mIoU) for all the three datasets obtained by the different approaches.
We achieve the best performance on all three datasets with a 14.8%, 10.0% and 7.7% relative improvement in mIoU over the source model on the GTA5 [1]} \(\rightarrow \)  Cityscapes [2]} and SYNTHIA [3]} \(\rightarrow \)  Cityscapes and [4]} \(\rightarrow \)  SUN [5]} respectively. This demonstrates how a light weight statistics update, which is applicable in the challenging SITA setting, could lead to a significant improvement in performance, with a minimal increase in inference time (Figure REF ).
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